It is known that all objects with a temperature above absolute zero emit thermal energy and that the intensity of the emission depends on the temperature of the object. In principle, the higher the temperature of the object, the greater is the intensity of the thermal emission from the object.
Thermal imaging systems utilize thermal sensors, such as micro-bolometers, to visualize heat differences within a scene by converting detected thermal energy into electrical energy to produce a thermal image or a thermal video of the scene. Hence, thermal imaging systems may, for example, provide thermal images in which a warm object such as a human stands out against a cooler background. Thermal imaging systems are, moreover, advantageous to use, compared to imaging systems utilizing visual light, as objects in a scene may be detected with or without illumination at the scene. Thermal imaging systems may further mitigate problems associated with complex light conditions such as when shadows or backlighting are present at the scene. Thermal imaging systems are thus frequently used in surveillance applications during day and night.
Detection and/or identification of an object of interest, such as a human, in a scene may, however, be problematic to achieve. A wide spread in temperatures for the objects within a scene may reduce the contrast such that it is difficult to distinguish an object of interest among other objects in a scene having similar thermal emission, e.g. if the object of interest has a similar temperature as that of its background.
A reduction of the dynamic range of the thermal data within the thermal imaging systems prior to displaying the thermal image may further reduce the detectability of the object of interest. Hence, there is a need for improved detection capability of thermal imaging systems.